ProjectPro

JUNE 6, 2025

Data engineering tools are specialized applications that make building data pipelines and designing algorithms easier and more efficient. These tools are responsible for making the day-to-day tasks of a data engineer easier in various ways. It can also access structured and unstructured data from various sources.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JUNE 6, 2025

FAQs on Data Engineering Skills Mastering Data Engineering Skills: An Introduction to What is Data Engineering Data engineering is the process of designing, developing, and managing the infrastructure needed to collect, store, process, and analyze large volumes of data.

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Let's delve deeper into the essential responsibilities and skills of a Big Data Developer: Develop and Maintain Data Pipelines using ETL Processes Big Data Developers are responsible for designing and building data pipelines that extract, transform, and load (ETL) data from various sources into the Big Data ecosystem.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Source Code: Build a Similar Image Finder Top 3 Open Source Big Data Tools This section consists of three leading open-source big data tools- Apache Spark , Apache Hadoop, and Apache Kafka. In Hadoop clusters , Spark apps can operate up to 10 times faster on disk. Hadoop, created by Doug Cutting and Michael J.

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

ProjectPro

JUNE 6, 2025

Table of Contents What is Real-Time Data Ingestion? Data Collection The first step is to collect real-time data (purchase_data) from various sources, such as sensors, IoT devices, and web applications, using data collectors or agents. Storage And Persistence Layer Once processed, the data is stored in this layer.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

ProjectPro

JUNE 6, 2025

Hadoop Datasets: These are created from external data sources like the Hadoop Distributed File System (HDFS) , HBase, or any storage system supported by Hadoop. RDDs provide fault tolerance by tracking the lineage of transformations to recompute lost data automatically. a list or array) in your program.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase , Apache Hive, and others like the Hadoop Distributed File System. To embark on the repository: [link] 9.

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

With global data creation expected to soar past 180 zettabytes by 2025, businesses face an immense challenge: managing, storing, and extracting value from this explosion of information. Traditional data storage systems like data warehouses were designed to handle structured and preprocessed data.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 40

NoSQL Database Hadoop Big Data 40

ProjectPro

JUNE 6, 2025

The next in the series of articles highlighting the most commonly asked Hadoop Interview Questions, related to each of the tools in the Hadoop ecosystem is - Hadoop HDFS Interview Questions and Answers. HDFS vs GFS HDFS(Hadoop Distributed File System) GFS(Google File System) Default block size in HDFS is 128 MB.

Hadoop 40

Hadoop Metadata Big Data Portfolio 40

Monte Carlo

OCTOBER 31, 2024

In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development. Data Storage Solutions As we all know, data can be stored in a variety of ways.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. What is Hadoop? This is not.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Analytics Vidhya

MARCH 7, 2023

Introduction Apache Flume is a tool/service/data ingestion mechanism for gathering, aggregating, and delivering huge amounts of streaming data from diverse sources, such as log files, events, and so on, to centralized data storage. Flume is a tool that is very dependable, distributed, and customizable.

Data Ingestion 223

Data Ingestion Data Storage Hadoop Data 223

ProjectPro

JUNE 6, 2025

Source: Microsoft Official Website Key Features of ADF Data Orchestration and Transformation : ADF empowers users to compose, schedule, and manage data pipelines that can move data between supported data stores. This service enables smooth, scalable data processing, leveraging Azure's global resources.

ETL Tools 40

ETL Tools Data Engineering Data Engineer Data Lake 40

ProjectPro

JUNE 6, 2025

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? ironSource has to collect and store vast amounts of data from millions of devices. ironSource started making use of Upsolver as its data lake for storing raw event data. Is Hadoop a data lake or data warehouse?

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

Knowledge Hut

APRIL 25, 2024

Check out the Big Data courses online to develop a strong skill set while working with the most powerful Big Data tools and technologies. Look for a suitable big data technologies company online to launch your career in the field. What Are Big Data T echnologies? Let's check the big data technologies list.

Big Data 98

Big Data Technology NoSQL Hadoop 98

ProjectPro

JUNE 4, 2015

All the components of the Hadoop ecosystem, as explicit entities are evident. All the components of the Hadoop ecosystem, as explicit entities are evident. The holistic view of Hadoop architecture gives prominence to Hadoop common, Hadoop YARN, Hadoop Distributed File Systems (HDFS ) and Hadoop MapReduce of the Hadoop Ecosystem.

Hadoop 52

Hadoop Architecture IT Java 52

ProjectPro

JUNE 6, 2025

So, let’s dive into the list of the interview questions below - List of the Top Amazon Data Engineer Interview Questions Explore the following key questions to gauge your knowledge and proficiency in AWS Data Engineering. Become a Job-Ready Data Engineer with Complete Project-Based Data Engineering Course !

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

ProjectPro

JUNE 6, 2025

ETL is a process that involves data extraction, transformation, and loading from multiple sources to a data warehouse, data lake, or another centralized data repository. An ETL developer designs, builds and manages data storage systems while ensuring they have important data for the business.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

As a Big Data Engineer, you shall also know and understand the Big Data architecture and Big Data tools. Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. You will get to learn about data storage and management with lessons on Big Data tools.

Big Data 40

Big Data Data Engineering Data Engineer Engineering 40

The Pragmatic Engineer

JUNE 13, 2023

The company’s largest data cluster is 20-30PB (petabytes: 1PB is 1,000 terabytes or 1M gigabytes). Ten years ago, this data cluster was 300GB as a Hadoop cluster; that’s around a 100,000-fold increase in data stored! The company runs 4 data centers: in the US and Europe, with two in Asia.

Cloud 242

Cloud Database Utilities BI 242

ProjectPro

JUNE 6, 2025

Features of PySpark Features that contribute to PySpark's immense popularity in the industry- Real-Time Computations PySpark emphasizes in-memory processing, which allows it to perform real-time computations on huge volumes of data. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

Big Data 40

Big Data Data Process Process Kafka 40

ProjectPro

JUNE 6, 2025

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. PaaS packages the platform for development and testing along with data, storage, and computing capability.

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

ProjectPro

JUNE 6, 2025

Increased Efficiency: Cloud data warehouses frequently split the workload among multiple servers. As a result, these servers handle massive volumes of data rapidly and effectively. Handle Big Data: Storage in cloud-based data warehouses may increase independently of computational resources. What is Data Purging?

Data Warehouse 40

Data Warehouse Data Mining Recruitment Database 40

ProjectPro

JUNE 6, 2025

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc. Briefly define COSHH.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

Christophe Blefari

JUNE 21, 2024

Both companies have added Data and AI to their slogan, Snowflake used to be The Data Cloud and now they're The AI Data Cloud. One way to read data platforms When we look at platforms history what characterises evolution is the separation (or not) between the engine and the storage. But what is doing Tabular?

Metadata 147

Metadata Data Warehouse BI MySQL 147

Knowledge Hut

DECEMBER 26, 2023

Most of the Data engineers working in the field enroll themselves in several other training programs to learn an outside skill, such as Hadoop or Big Data querying, alongside their Master's degree and PhDs. Kafka Kafka is an open-source processing software platform.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JUNE 6, 2025

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 40

Certification Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

It enables users to import and transform data from various on-premise and cloud-based services, release the transformed data, send it to a data storage or analytics engine, and analyze the data streams using a visual interface. Through Kafka connect, events from Kafka streams move to influxDB.

Data Engineering 40

Data Engineering Data Engineer Engineering Data Lake 40

Data Engineering Podcast

DECEMBER 16, 2019

Many metadata management systems are simply a service layer on top of a separate data storage engine. Many metadata management systems are simply a service layer on top of a separate data storage engine. Can you explain how Marquez is architected and how the design has evolved since you first began working on it?

Metadata 100

Metadata PostgreSQL Data Warehouse Datasets 100

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Kafka Architecture 40

ProjectPro

JULY 21, 2021

As a big data architect or a big data developer, when working with Microservices-based systems, you might often end up in a dilemma whether to use Apache Kafka or RabbitMQ for messaging. Rabbit MQ vs. Kafka - Which one is a better message broker? Table of Contents Kafka vs. RabbitMQ - An Overview What is RabbitMQ?

Kafka 52

Kafka Java Big Data Architecture 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78